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Mitigation Blocks

Warmup Window

Minimum bars needed: 2 × swing_length + 1 bars (default params: 11 bars (swing_length=5))

Requires confirmed swing pivots. After warmup, new mitigation blocks appear in real-time on every new bar.

✅ After the warmup window is filled, this indicator produces a new value on every incoming bar in real-time.

Real-time Indicator

Mitigation blocks appear after pivot confirmation, not after smoothing delay.

EventLagDetail
Mitigation block zone appears≈ swing_length bars after the pivotFirst same-direction candle of impulse to MSS; pivot needs swing_length bars
Signal fires when price returns to zone0 barsInstant once the zone exists

Mitigation Blocks identify the first candle that initiates an impulsive move leading to a Market Structure Shift — the origin of institutional order flow.

Concept (ICT / Smart Money):

  • While an Order Block is the last opposing candle before an impulse, a Mitigation Block is the first same-direction candle that starts the move.
  • Bullish Mitigation Block: After a bullish MSS (close breaks swing high with confirmed LL pattern), the first bullish candle (close > open) after the preceding swing low that kicked off the upward impulse.
  • Bearish Mitigation Block: After a bearish MSS (close breaks swing low with confirmed HH pattern), the first bearish candle (close < open) after the preceding swing high that kicked off the downward impulse.
  • When price returns to a Mitigation Block zone, institutional traders are "mitigating" (closing/adjusting) positions opened at that origin candle.

Signals:

  • Entry Long: Price retraces into the bullish MB zone (potential long entry)
  • Entry Short: Price retraces into the bearish MB zone (potential short entry)
  • Mitigated: Price closes through the opposite side of the zone (block invalidated)
def mitigation_blocks(
    data: Union[PdDataFrame, PlDataFrame],
    swing_length: int = 5,
    use_body: bool = False,
    high_column: str = "High",
    low_column: str = "Low",
    open_column: str = "Open",
    close_column: str = "Close",
) -> Union[PdDataFrame, PlDataFrame]:

Returns the following columns:

  • mb_bullish / mb_bearish: 1 when a Mitigation Block is established
  • mb_top / mb_bottom: Active MB zone boundaries (forward-filled)
  • mb_direction: 1 for bullish MB, -1 for bearish MB, 0 when no MB is active
  • mb_entry_long / mb_entry_short: 1 when price enters the MB zone
  • mb_mitigated: 1 when the MB zone is mitigated

Signal function:

  • mb_signal: 1 = long entry, -1 = short entry, 0 = no signal

Example

from investing_algorithm_framework import download

from pyindicators import (
    mitigation_blocks,
    mitigation_blocks_signal,
    get_mitigation_blocks_stats,
)

pd_df = download(
    symbol="btc/eur",
    market="bitvavo",
    time_frame="4h",
    start_date="2024-01-01",
    end_date="2024-06-01",
    pandas=True,
)

# Detect Mitigation Blocks
pd_df = mitigation_blocks(pd_df, swing_length=5)
pd_df = mitigation_blocks_signal(pd_df)

# Get summary statistics
stats = get_mitigation_blocks_stats(pd_df)
print(stats)

pd_df[["Close", "mb_bullish", "mb_bearish", "mb_top",
       "mb_bottom", "mb_entry_long", "mb_entry_short",
       "mb_signal"]].tail(10)

MITIGATION_BLOCKS

Chart Parameters

The image above uses the following parameters:

ParameterValue
swing_length5